6 articles
This article presents Google Cloud's cluster-level reliability framework for TPUs designed to optimize infrastructure availability for training trillion-parameter AI models at scale.
Google announces AI Hypercomputer, an integrated infrastructure stack optimized for the agentic era with next-generation TPUs, GPUs, networking, and storage systems.
Google introduces new AI infrastructure optimized for agentic AI systems that require unified compute, storage, and orchestration capabilities.
Google introduced eighth-generation TPUs (TPU 8t and TPU 8i) optimized for modern AI workloads with improved efficiency and scalability for training and serving.
Google's seventh-generation Ironwood TPU achieves a 3.7x improvement in Compute Carbon Intensity (CCI) compared to TPU v5p, demonstrating significant carbon efficiency gains in AI infrastructure.
This post provides a technical guide for developers on optimizing AI model training using Google's seventh-generation Ironwood TPU within the JAX and MaxText ecosystems.
